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\title{Nehovah: The Great ``I am'' of Neologisms}
\author{Mike Smith and Ryan Hintze\\Department of Computer Science\\Brigham Young University}
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The goal of this project is to generate novel words (neologisms) given a set of words.
Our system (\textit{Nehovah}), abstracts concepts related to the provided words using WordNet\cite{wordnet} and other sources to generate a set of candidate words.
Nehovah explores the space of neologisms by combining the prefixes and suffixes from the set of candidate words and returns a set of neologisms with an associated score.
The score is calculated based on the absence of awkward combinations of letter in a neologism, how well the neologism captures the senses of the original words, and how ``catchy'' the neologism is.
The ``awkwardness'' of a combination of letters is determined using \textit{n}-gram frequency counts obtained from WordNet.
The frequencies from WordNet also provide information about how common a combination of letters appear as prefixes and/or suffixes.
The primary challenge with Nehovah is determining how ''catchy`` a generated neologism is.
We define catchiness to include (but not be limited to) sounding like commonly used words which also portray a double entendre.
Ultimately, we intend for Nehovah to include pop culture through the integration of social media applications such as Twitter.
 
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